• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.174-174
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• 2017

To cope with phosphate (Pi) deficient stress, plants modulate various physiological and developmental processes, such as gene expression, Pi uptake and translocation, and root architecture changes. Here, we report the identification and characterization of novel activation-tagged mutant involved in Pi starvation signaling in Arabidopsis. The hpd (${\underline{h}ypersensitive}$ to ${\underline{P}i}$ $ {\underline{d}eficiency}$) mutant exhibits enhanced phosphate uptake and altered root architectural change under Pi starvation compared to wild type. Expression analysis of auxin-responsive DR5::GUS reporter gene in hpd mutant indicated that auxin translocation in roots under Pi starvation are suppressed in hpd mutant plants. Impaired auxin translocation in roots of hpd mutant was attributable to abnormal root architecture changes in Pi starvation conditions. Our results indicated that abnormal auxin translocation in hpd mutant might be due to mis-regulation of auxin efflux carrier proteins, PIN-FORMED (PIN) 1, and 2 under Pi starvation conditions. Not only expression levels but also expression domains of PIN proteins were altered in hpd mutant in response to Pi starvation. Molecular genetic analysis of hpd mutant revealed that the mutant phenotype is caused by the lesion in ENHANCED SILENCING PHENOTYPE4 (ESP4) gene whose function is proposed in mRNA 3'-end processing. The results suggest that mRNA processing plays crucial roles in Pi homeostasis as well as developmental reprograming in response to Pi deprivation in Arabidopsis.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2891-2893
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• 2005

In this paper, we introduce a new category of Self-Organizing Fuzzy Polynomial Neural Networks (SOFPNN) that is based on a genetically optimized multi-layer perceptron with fuzzy polynomial neurons (FPNs) and discuss its comprehensive design methodology involving mechanisms of genetic optimization. The conventional SOFPNN algorithm leads to a tendency to produce overly complex networks as well as a repetitive computation load by the trial and error method and/or the a repetitive parameter adjustment by designer. In order to generate a structurally and parametrically optimized network, such parameters need to be optimal. In this study, in solving the problems with the conventional SOFPNN, we introduce a new design approach of evolutionary optimized SOFPNN. Optimal parameters design available within FPN (viz. the no. of input variables, the order of the polynomial, input variables, and the no. of membership function) lead to structurally and parametrically optimized network which is more flexible as well as simpler architecture than the conventional SOFPNN. In addition, we determine the initial apexes of membership functions by genetic algorithm.

• Smart Structures and Systems
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• v.18 no.4
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• pp.819-837
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• 2016

The quality of vibration pattern reproduction of elastic structures by the modal expansion method is influenced by the modal expansion method and the sensor placement as well as the accuracy of measured natural modes and the total number of vibration sensors. In this context, this paper presents an improved numerical method for reproducing the vibration patterns by introducing a block-wise modal expansion method (BMEM), together with the genetic algorithm (GA). For a given number of vibration sensors, the sensor positions are determined by an evolutionary optimization using GA and the modal assurance criterion (MAC). Meanwhile, for the proposed block-wise modal expansion, a whole frequency range of interest is divided into several overlapped frequency blocks and the vibration field reproduction is made block by block with different natural modes and different modal participation factors. A hollow cylindrical tank is taken to illustrate the proposed improved modal expansion method. Through the numerical experiments, the proposed method is compared with several conventional methods to justify that the proposed method provides the improved results.

• Journal of Ocean Engineering and Technology
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• v.34 no.4
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• pp.272-276
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• 2020

This paper presents an optimization process for a catamaran hull form. The entire optimization process was managed using the CAD-CFD integration platform CAESES. The resistance of the demi-hull was simulated in calm water using the CFD solver STAR-CCM+, and an inviscid fluid model was used to reduce the computing time. The Free-Form Deformation (FFD) method was used to make local changes in the bulbous bow. For the optimization of the bulbous bow, the Non-dominated Sorting Genetic Algorithm (NSGA)-II was applied, and the optimization variables were the length, breadth, and angle between the bulbous bow and the base line. The Lackenby method was used for global variation of the bow of the hull. Nine hull forms were generated by moving the center of buoyancy while keeping the displacement constant. The optimum bow part was selected by comparing the resistance of the forms. After obtaining the optimum demi-hull, the distance between two demi-hulls was optimized. The results show that the proposed optimization sequence can be used to reduce the resistance of a catamaran in calm water.

• Journal of Korean Association for Spatial Structures
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• v.15 no.2
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• pp.105-112
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• 2015

A shared tuned mass damper (STMD) was proposed in previous research for reduction of dynamic responses of the adjacent buildings subjected to earthquake loads. A single STMD can provide similar control performance in comparison with two traditional TMDs. In previous research, a passive damper was used to connect the STMD with adjacent buildings. In this study, a smart magnetorheological (MR) damper was used instead of a passive damper to compose an adaptive smart STMD (ASTMD). Control performance of the ASTMD was investigated by numerical analyses. For this purpose, two 8-story buildings were used as example structures. Multi-input multi-output (MIMO) fuzzy logic controller (FLC) was used to control the command voltages sent to two MR dampers. The MIMO FLC was optimized by a multi-objective genetic algorithm. Numerical analyses showed that the ASTMD can effectively control dynamic responses of adjacent buildings subjected to earthquake excitations in comparison with a passive STMD.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2821-2823
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• 2002

In this paper we propose the Multi-FNN (Fuzzy-Neural Networks) for optimal identification modeling of complex system. The proposed Multi-FNNs is based on a concept of FNNs and exploit linear inference being treated as generic inference mechanisms. In the networks learning, backpropagation(BP) algorithm of neural networks is used to updata the parameters of the network in order to control of nonlinear process with complexity and uncertainty of data, proposed model use a HCM(Hard C-Means)clustering algorithm which carry out the input-output dat a preprocessing function and Genetic Algorithm which carry out optimization of model The HCM clustering method is utilized to determine the structure of Multi-FNNs. The parameters of Multi-FNN model such as apexes of membership function, learning rates, and momentum coefficients are adjusted using genetic algorithms. An aggregate performance index with a weighting factor is proposed in order to achieve a sound balance between approximation and generalization abilities of the model. NOx emission process data of gas turbine power plant is simulated in order to confirm the efficiency and feasibility of the proposed approach in this paper.

• Journal of the Society of Naval Architects of Korea
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• v.48 no.2
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• pp.178-182
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• 2011

Generally in order to reduce the steel weight of stiffened plate, stiffener spaces tend to be narrow and the plate gets thin. However, it will involve more fabrication cost because it can lead to the increase of welding length and the number of structural members. In the yard, the design which is able to reduce the total fabrication cost is needed, although it requires more steel weight. The purpose of this study is to find optimum stiffener spaces to minimize the fabrication cost for the cargo tank of LPG Carriers. Global optimization methods such as ES(Evolution Strategy) and GA(Genetic Algorithm) are introduced to find a global optimum solution and the sum of steel material cost and labor cost is selected as main objective function. Convergence degree of both methods in according to the size of searching population is examined and an efficient size is investigated. In order to verify the necessity of the optimum design based on the cost, minimum weight design and minimum cost design are carried out.

• International Journal of Naval Architecture and Ocean Engineering
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• v.7 no.1
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• pp.142-156
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• 2015

A new method for ship Inner Shell optimization, which is called Parametric Inner Shell Optimization Method (PISOM), is presented in this paper in order to improve both hull performance and design efficiency of transport ship. The foundation of PISOM is the parametric Inner Shell Plate (ISP) model, which is a fully-associative model driven by dimensions. A method to create parametric ISP model is proposed, including geometric primitives, geometric constraints, geometric constraint solving etc. The standard optimization procedure of ship ISP optimization based on parametric ISP model is put forward, and an efficient optimization approach for typical transport ship is developed based on this procedure. This approach takes the section area of ISP and the other dominant parameters as variables, while all the design requirements such as propeller immersion, fore bottom wave slap, bridge visibility, longitudinal strength etc, are made constraints. The optimization objective is maximum volume of cargo oil tanker/cargo hold, and the genetic algorithm is used to solve this optimization model. This method is applied to the optimization of a product oil tanker and a bulk carrier, and it is proved to be effective, highly efficient, and engineering practical.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.37 no.9
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• pp.38-46
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• 2000

In this paper, a grating to apply for the optical interconnection is designed using a Genetic Algorithm(GA) as a robust and an efficient schema. A hybrid optical interconnection system architecture is implemented by the liquid crystal panel as a programmable spatial light modulator. As the result of geometrical transformation to obtain the quantitative data for $3{\times}3$ spot beams at CCD array detector by optical experiment truthfully, the mean of beam intensity as a gray level is 202, the maximum value is 225, the minimum value is 186, and a uniformity is quantitatively $1.93{\times}10^{-1}$ similar to simulation result.

• Journal of information and communication convergence engineering
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• v.19 no.2
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• pp.114-119
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• 2021

This paper proposes a method to find an optimal T' with the most terminal of the subset of T' trees that can be connected by a given length by improving a memetic genetic algorithm within several constraints, when the set of terminal T is given to the Euclidean plane R². Constraint (1) is that a given length cannot connect all terminals of T, and (2) considers only the rectilinear layout of the edge connecting each terminal. The construction of interconnections has been used in various design-related areas, from network to architecture. Among these areas, there are cases where only the rectilinear layout is considered, such as wiring paths in the computer network and VLSI design, network design, and circuit connection length estimation in standard cell deployment. Therefore, the heuristics proposed in this paper are expected to provide various cost savings in the rectilinear layout.